TL;DR: Together Computer open-sourced HybridAgent, an agent framework where the model reasons in continuous latent space but still acts through text, cutting the token overhead of explicit chain-of-thought.
Summary: Together Computer published HybridAgent, a framework for LLM agents that interleave latent-space 'thinking' with text-based actions instead of verbalizing every reasoning step. The release ships code on GitHub, a companion model collection on Hugging Face, and evaluation results in an accompanying arXiv paper. It targets the core inefficiency of text-only reasoning traces, where long chains of thought burn tokens and context before any tool call happens.
Why it matters: Latent reasoning could cut inference cost and latency for multi-step agents while keeping tool use interpretable through text actions. Worth cloning the repo and checking the paper's evals to see whether latent thinking holds up on your own agentic benchmarks.
Source: rss